class_docstr: Keeps track of a running mean for seen states.
  
  The filter will be used to normalize observations and will be 
  online updated according to the seen observations of all actors.
code: def __call__(self, x, update=True):
      x = np.asarray(x)
      if update:
          if len(x.shape) == len(self.rs.shape) + 1:
              # The vectorized case.
              for i in range(x.shape[0]):
                  self.rs.push(x[i])
                  self.buffer.push(x[i])
          else:
              # The unvectorized case.
              self.rs.push(x)
              self.buffer.push(x)
      if self.demean:
          x = x - self.rs.mean
      if self.destd:
          x = x / (self.rs.std + 1e-8)
      if self.clip:
          x = np.clip(x, -self.clip, self.clip)
      return x
  
imports: import numpy
label_desc: Use image node_id 7 for calling the MeanStdFilter obj's underlying member method code with example usage: obj.__call__(x, update) and returns: x